Data Science Supervisor

Data Science - Supervisor

Headquartered in Dublin, Ohio, Cardinal Health, Inc. (NYSE: CAH) is a global, integrated healthcare services and products company connecting patients, providers, payers, pharmacists and manufacturers for integrated care coordination and better patient management. Backed by nearly 100 years of experience, with more than 50,000 employees in nearly 60 countries, Cardinal Health ranks among the top 20 on the Fortune 500.

Department Overview

AI & Data Science team builds analytics and artificial intelligence solutions that drive success for Cardinal Health by creating material savings, efficiencies and revenue growth opportunities. The team drives business innovation by leveraging emerging technologies and turning them into differentiating business capabilities.

Job Overview

The primary role of the Data Science Supervisor is to oversee the post-deployment operations, continuous optimization, and operational performance of Agentic AI and Intelligent Automation solutions within the Finance Digital Solutions portfolio. This role will lead the operational Run” phase, ensuring that generative AI agents, Large Language Model (LLM) integrations, and production workflows remain highly available, secure, and accurate. This position collaborates closely with offshore/onshore developers, data scientists, and business partners to manage risk, solve complex problems, and deliver long-term support for mission-critical solutions.

Responsibilities

• Lead the ongoing operations, maintenance, and performance evaluation of production Agentic AI engines, FastAPI/Flask services, and Python-based analytical pipelines.
• Ensure production databases and connections to enterprise systems (such as SAP, Salesforce, and Postgres) are maintained, secure, and highly optimized.
• Establish best practices for Agent Observation, Evaluation, and prompt maintenance to adapt to shifting financial processes and business rules.
• Work with cross-functional partners across our highly matrixed organization to understand both upstream inputs to, and downstream impact of, current and future operational processes.
• Align technical specifications and post-deployment modifications with business needs and enterprise security standard guidelines.
• Act as a techno-functional leader, generating ideas for process and platform improvements and ensuring data compliance standards are met.
• Provides direct supervision and leadership to team
• Strategize and prioritize responsibilities of direct reports
• Assess business opportunities and promote use of data science, analytics within domain and build internal and external resources and expertise.
• A part of the role also requires to be hands-on and working together with external and internal partners to develop, test and operationalize data science and analytical solutions as well as ensure its adoption by businesses.
• Work to leverage data (Transactional / Big Data, External/ Internal Data, Structured/ Unstructured Data) and analytics methods to develop analytics solutions

Qualifications

• 6 - 8 years of AI & data science experience preferred, including 2-3 years of direct people management experience (direct people reporting)
• BTech-BE from Tier 1/2 engineering schools or MStat/MS (Math)/MA Econ/ MS Analytics/data science from Tier 1/2 schools
• Deep expertise in Google Cloud Platform (GCP) technologies, including Cloud SQL, BigQuery, and GCP Cloud Functions.
• Advanced proficiency in Python (specifically FastAPI, Flask) and SQL.
• Direct experience with Agentic AI architectures, Prompt Engineering, Agent Evaluation, and Agent Observation.
• Strong knowledge of containerization and orchestration using Kubernetes.
• Experience integrating and maintaining connections to enterprise databases and applications like Postgres, SAP, and Salesforce.
• Design ML/LLM pipelines, good knowledge of RAG, prompt engineering.
• Monitor system performance, logs, retrieval quality and prompt-effectiveness
• Integrate microservices with ApigeeX for API management, security (authentication, authorization, rate limiting), monitoring, and analytics.
• Skills in areas like Agentic AI, GenAI, and some other traditional AI techniques like optimization, Statistics, Machine learning, NLP, Image/ Video, Speech analytics
• Preferably good knowledge of Agile & SCRUM development processes

Soft Skills

• Coach and Mentor data science operations Team members
• Excellent communication and storytelling skills (oral, written and presentation)
• Highly driven, energetic, flexible & ability to multitask
• Ability to work with teams/ stakeholders to drive change/ adoption of analytics solutions